Omnidirectional vision for visual landmark identification using p/sup 2/-invariants

The automatic landmark identification is very important in autonomous robot navigation tasks. In this work we use a monocular omnidirectional vision system to extract images features, and with help of the conformal geometric algebra, we show how these features can be used to calculate projective and permutation p²-invariants. These p²-invariants represent scene sub-landmarks and a set of them characterize a landmark. The advantage of this representation is that the landmarks are more robust than the single cross-ratio